hb | Harbour fork + | Binary Executable Format library
kandi X-RAY | hb Summary
kandi X-RAY | hb Summary
Harbour fork (from + updates & fixes = 3.4
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Currently covering the most popular Java, JavaScript and Python libraries. See a Sample of hb
hb Key Features
hb Examples and Code Snippets
:: MinGW-w64 LLVM/Clang via MSYS2 (x86 target)
set PATH=C:\msys64\mingw32\bin;C:\msys64\usr\bin;%PATH%
set HB_COMPILER=clang
mingw32-make
:: MinGW-w64 LLVM/Clang via MSYS2 (x64 target)
:: (requires preceding build for x86 target)
set PATH=C:\msys64\
:: MinGW-w64 LLVM/Clang via MSYS2 (x86 target)
set PATH=C:\msys64\mingw32\bin;C:\msys64\usr\bin;%PATH%
set HB_COMPILER=clang
mingw32-make
:: MinGW-w64 LLVM/Clang via MSYS2 (x64 target)
set PATH=C:\msys64\mingw64\bin;C:\msys64\usr\bin;%PATH%
set HB_C
$ package/mpkg_rpm.sh
--with static - link all binaries with static libs
--with localzlib - build local copy of zlib library
--with localpcre2 - build local copy of pcre2 library
--with localpcre1 - build local copy of pcre1 library
--witho
Community Discussions
Trending Discussions on hb
QUESTION
Update: Added a simpler demonstration jsfiddle, https://jsfiddle.net/47sfj3Lv/3/.
reproducing the problem in much less code I'm trying to move away from jQuery.
Some of my code, for populating some tables, has code like this
...ANSWER
Answered 2021-Jun-15 at 18:27This was difficult for me to understand, so I wanted to share if anyone else has the same issue.
It seems that an async method will break a method chain, there's no way around that. And since fetch is asynchronous, await must be used, and in order for await to be used, the calling method must be declared async. Thus the method chain will be broken.
The way the method chain is called must be changed.
In my OP, I linked https://jsfiddle.net/47sfj3Lv/3/ as a much simpler version of the same problem. StackOverflow's 'fiddle' effectively blocks 'fetch' for security reasons, so I need to use JSFiddle for demonstration.
Here's a working version of the same code using then
and how/why it works, and a slightly shorter version, because await can be specified with the the fetch, obviously.
QUESTION
i'm new to R and shiny and also new to this forum.
I need to build a shiny app but struggle to connect the inputs with my imported data.
This is what i have so far:
...ANSWER
Answered 2021-Jun-13 at 21:19Tidyverse solution: You use your inputs to filter the dataset, right before plotting it. Therefore you need to get the data in long format with tidyr::pivot_longer()
before.
Afterwards you can filter here:
QUESTION
I am getting 40 key & value data when the user submits the from. Like below.
...ANSWER
Answered 2021-Jun-05 at 18:04This is how it can be done.
QUESTION
I have two JPA-entities:
...ANSWER
Answered 2021-Jun-05 at 15:28solution suggested from comments
QUESTION
`CREATE TABLE PERSON
(
Person_id NUMBER(3) PRIMARY KEY,
Surname VARCHAR2(20),
First_name VARCHAR2(20),
Sex CHAR(1),
Birth_date DATE,
Street VARCHAR2(40),
Town CHAR(20),
Postcode NUMBER(4),
Next_of_kin NUMBER(3)
);
CREATE TABLE STAFF
(
Person_id NUMBER(3) PRIMARY KEY,
Start_date DATE,
Staff_type VARCHAR2(15),
Charges NUMBER(10,2),
Resign_date DATE,
FOREIGN KEY (Person_id) references PERSON(Person_id)
);
CREATE TABLE WARD (
Ward_code CHAR(3) PRIMARY KEY,
Ward_name VARCHAR2(20),
Bed_count NUMBER(4),
Opened_date DATE,
Last_painted_date DATE,
Daily_charge NUMBER(10,2)
);
CREATE TABLE OPERATION_TYPE (
Op_code CHAR(3) PRIMARY KEY,
Operation_name VARCHAR2(50),
Theatre_fee NUMBER(10,2),
Days_in NUMBER(5)
);
CREATE TABLE ADMISSION (
Admission_id NUMBER(3) PRIMARY KEY,
Patient_id NUMBER(3),
Admission_date DATE NOT NULL,
Expected_op CHAR(3),
Admitted_by NUMBER(3),
Ward_code CHAR(3),
Discharge_date DATE,
FOREIGN KEY (Patient_id) references PERSON(Person_id),
FOREIGN KEY (Expected_op) references OPERATION_TYPE(Op_code),
FOREIGN KEY (Admitted_by) references PERSON(Person_id),
FOREIGN KEY (Ward_code) references WARD(Ward_code)
);
CREATE TABLE OPERATION (
Operation_id NUMBER(3) PRIMARY KEY,
Actual_op CHAR(3),
Admission_id NUMBER(3),
Op_date DATE,
Surgeon NUMBER(3),
Anaesthetist NUMBER(3),
FOREIGN KEY (Surgeon) references PERSON(Person_id),
FOREIGN KEY (Anaesthetist) references PERSON(Person_id),
FOREIGN KEY (Actual_op) references OPERATION_TYPE(Op_code),
FOREIGN KEY (Admission_id) references ADMISSION(Admission_id)
);
CREATE TABLE OBSERVATION(
Admission_id NUMBER(3),
Observ_date DATE,
Observ_time NUMBER(4),
Observ_type CHAR(10),
Observ_value NUMBER(4),
Staff_id NUMBER(3),
PRIMARY KEY (Admission_id,Observ_date,Observ_time,Observ_type),
FOREIGN KEY (Admission_id) references ADMISSION(Admission_id),
FOREIGN KEY (Staff_id) references STAFF(Person_id)
);
REM***********************
REM PERSON TABLE
REM***********************
INSERT INTO PERSON VALUES (101,'Black','Barry','M','31/12/1959','11 High St.','Cooma',2630,102);
INSERT INTO PERSON VALUES (102,'Black','Mary','F','11/04/1965','11 High St.','Cooma',2630,NULL);
INSERT INTO PERSON VALUES (103,'Strathclyde','Albert','M','15/5/1955','3 The Mews','Hawthorne',3171,104);
INSERT INTO PERSON VALUES (104,'Strathclyde','Alice','F','17/7/1955','3 The Mews','Hawthorne',3171,103);
INSERT INTO PERSON VALUES (105,'Green','Gill','F','16/6/1966','124 Main St.','Young',2594,106);
INSERT INTO PERSON VALUES (106,'Green','Graham','M','24/4/1967','124 Main St.','Young',2594,105);
INSERT INTO PERSON VALUES (107,'Gray','Lesley','F','12/9/1972','130 Main St.','Young',2594,109);
INSERT INTO PERSON VALUES (109,'Gray','John','M','14/4/1972','130 Main St.','Young',2594,107);
INSERT INTO PERSON VALUES (110,'Samuelson','Thomas','M','1/1/1964','17 The Mews','Hawthorne',3171,NULL);
INSERT INTO PERSON VALUES (111,'Abrahams','Mary','F','15/5/1967','2177A The Esplanade','Ivanhoe',3878,NULL);
INSERT INTO PERSON VALUES (112,'Aumann','Monica','F','25/5/1955','29 The Esplanade','Ivanhoe',3878,NULL);
INSERT INTO PERSON VALUES (113,'Brown','Melissa','F','8/8/1984','11 East St.','Cooma',2630,NULL);
INSERT INTO PERSON VALUES (114,'Napier','Mary','F','1/1/1971','163 New Rd.','Henty',2658,NULL);
INSERT INTO PERSON VALUES (115,'Nelson','Nigel','M','2/2/1972','165 Young Rd.','Temora',2666,NULL);
INSERT INTO PERSON VALUES (116,'Newman','Olive','F','3/3/1973','21 Olympic Way','Henty',2658,NULL);
INSERT INTO PERSON VALUES (117,'Gray','Lesley','M','31/12/1989','130 Andres St.','Young',2594,105);
INSERT INTO PERSON VALUES (118,'Hon','Tasuku','M','13/3/1953','21 Silcon Height','Henty',2658,NULL);
INSERT INTO PERSON VALUES (119,'Livingstone','Frank','M','3/3/2003','21 Sun Height','Henty',2658,122);
INSERT INTO PERSON VALUES (120,'Giggle','Frank','M','23/3/1975','21 Albrige Close','Cooma',2630,121);
INSERT INTO PERSON VALUES (121,'Giggle','Felicia','F','3/3/1980','21 Albrige Close','Cooma',2630,120);
INSERT INTO PERSON VALUES (122,'Black','Frank Jr','M','13/3/2011','21 Stun Height','Henty',2658,123);
INSERT INTO PERSON VALUES (123,'Black','Frances','F','12/12/2005','21 Stun Height','Henty',2658,122);
INSERT INTO PERSON VALUES (124,'Smith','Buddy','M','11/12/1979','101 High St.','Cooma',2630,NULL);
INSERT INTO PERSON VALUES (125,'Smith','Maxime','F','31/12/1979','101 High St.','Cooma',2630,124);
INSERT INTO PERSON VALUES (126,'Smith','Issac','M','1/12/2007','101 High St.','Cooma',2630,124);
INSERT INTO PERSON VALUES (127,'Smith','Ronny','M','3/12/2009','101 High St.','Cooma',2630,124);
INSERT INTO PERSON VALUES (128,'Giggle','Fanny','F','3/12/2007','121 Close Rose','Hillo',2330,120);
INSERT INTO PERSON VALUES (129,'Murad','Nadia','F','3/3/2000','121 Close Rose', 'Hillo',2330,130);
INSERT INTO PERSON VALUES (130,'Murad','Tange','M','3/3/1999','7711 Albrige Close','Cooma',2630,NULL);
INSERT INTO PERSON VALUES (131,'Rome','Paula','F','23/9/1965','21 Height Close','Cooma',2630,132);
INSERT INTO PERSON VALUES (132,'Rome','Paul','M','13/3/1966','21 Height Close','Cooma',2630,NULL);
INSERT INTO PERSON VALUES (133,'Rome','Fay','M','3/3/2017','21 Height Close','Cooma',2630,132);
INSERT INTO PERSON VALUES (134,'Murad','Michelle','F','3/3/2001','1 Height Close','Cooma',2630,NULL);
INSERT INTO PERSON VALUES (135,'Trump','Donald','M','13/3/1956','222 White House Avenue','Cooma',2630,NULL);
INSERT INTO PERSON VALUES (136,'Trump','Melania','F','3/3/1992','222 White House Avenue','Cooma',2630,135);
INSERT INTO PERSON VALUES (137,'Trump','Baron','M','3/6/2005','222 White House Avenue','Cooma',2630,135);
INSERT INTO PERSON VALUES (138,'Johnson','Boris','M','23/9/1965','10 Downing Street','Wagga Wagga',2999,NULL);
INSERT INTO PERSON VALUES (139,'Cordeiro','Wayne','M','3/3/1965','777 Hawaii Close Rose', 'Hillo',7770, NULL);
INSERT INTO PERSON VALUES (140,'Cordeiro','Anne','F','23/4/1968','777 Hawaii Close Rose', 'Hillo',7770, 139);
INSERT INTO PERSON VALUES (141,'Thatcher','Margaret','F','21/1/1955','120 Main Sq.','Wagga Wagga',2999,142);
INSERT INTO PERSON VALUES (142,'Thatcher','Denis','M','23/9/1955','120 Main Sq.','Wagga Wagga',2999,NULL);
INSERT INTO PERSON VALUES (143,'Thatcher','Carols','F','1/9/1985','120 Main Sq.','Wagga Wagga',2999,142);
INSERT INTO PERSON VALUES (144,'Nelson','Nigel','M','22/2/1992','15 Young Rd.','Temora',2666,NULL);
INSERT INTO PERSON VALUES (145,'Neon','Gela','F','2/2/1972','1465 Main Rd.','Temora',2666,NULL);
INSERT INTO PERSON VALUES (146,'Twain','Shane','F','21/1/1995','A-129 Main Rose Sq.','Wagga Wagga',2650,147);
INSERT INTO PERSON VALUES (147,'Twain','Dens','M','23/9/1985','A-129 Main Rose Sq.','Wagga Wagga',2650,NULL);
INSERT INTO PERSON VALUES (148,'Trump','Ivanka','F','5/3/1985','222 White House Avenue','Cooma',2630,135);
INSERT INTO PERSON VALUES (149,'Trump','Eric','M','3/12/1975','222 White House Avenue','Cooma',2630,135);
INSERT INTO PERSON VALUES (150,'Gates','Bill','M','5/3/1975','2 Rosey Lane','Cooma',2630,NULL);
INSERT INTO PERSON VALUES (151,'Bucket','Eric','M','3/1/1985','11 Oserey Avenue','Cooma',2630,NULL);
REM*******************************************************
REM STAFF TABLE
REM nursing services will not be charged to the patients
REM*******************************************************
INSERT INTO STAFF VALUES (103,'1/1/2009','Surgeon',4525,NULL);
INSERT INTO STAFF VALUES (110,'5/5/2009','Surgeon',5600,NULL);
INSERT INTO STAFF VALUES (118,'1/5/2016','Surgeon',7890,NULL);
INSERT INTO STAFF VALUES (111,'1/1/2009','Anaesthetist',5900,NULL);
INSERT INTO STAFF VALUES (112,'3/3/2009','Anaesthetist',4788,NULL);
INSERT INTO STAFF VALUES (114,'1/1/2009','Senior Nurse',NULL,NULL);
INSERT INTO STAFF VALUES (115,'2/2/2016','Nurse',NULL,NULL);
INSERT INTO STAFF VALUES (116,'3/3/2014','Nurse',NULL,NULL);
INSERT INTO STAFF VALUES (125,'23/3/2014','Nurse',NULL,NULL);
INSERT INTO STAFF VALUES (135,'1/1/2019','Senior Nurse',NULL,NULL);
INSERT INTO STAFF VALUES (136,'2/2/2016','Nurse',NULL,NULL);
INSERT INTO STAFF VALUES (138,'23/3/2019','Nurse',NULL,NULL);
INSERT INTO STAFF VALUES (139,'23/3/2020','Senior Nurse',NULL,NULL);
INSERT INTO STAFF VALUES (150,'1/11/2019','Anaesthetist',6900,NULL);
INSERT INTO STAFF VALUES (151,'31/1/2019','Anaesthetist',5900,NULL);
REM***********************
REM WARD TABLE
REM***********************
INSERT INTO WARD VALUES ('C','Covid Bay',90,'31/12/2019',NULL,150.00);
INSERT INTO WARD VALUES ('A','Abraham',80,'1/12/2015','12/05/2011',350.00);
INSERT INTO WARD VALUES ('N','Nightingale',50,'1/12/2017','12/05/2012',450.00);
INSERT INTO WARD VALUES ('F','Flemming',75,'15/11/2009',NULL,230.00);
INSERT INTO WARD VALUES ('L','Lister',80,'1/1/2009','20/12/2013',200.00);
INSERT INTO WARD VALUES ('P','Pasteur',60,'1/12/2009','12/12/2011',250.00);
REM***********************
REM OPERATION_TYPE TABLE
REM***********************
INSERT INTO OPERATION_TYPE VALUES ('LO','Lobotomy',700.00,10);
INSERT INTO OPERATION_TYPE VALUES ('CS','Caesarean',5700.00,3);
INSERT INTO OPERATION_TYPE VALUES ('CT','Cataract',670.00,1);
INSERT INTO OPERATION_TYPE VALUES ('AP','Appendicectomy',500.00,5);
INSERT INTO OPERATION_TYPE VALUES ('HB','Heart Bypass',2000.00,14);
INSERT INTO OPERATION_TYPE VALUES ('HT','Heart Transplant',5000.00,30);
INSERT INTO OPERATION_TYPE VALUES ('HY','Hysterectomy',800.00,7);
INSERT INTO OPERATION_TYPE VALUES ('LA','Leg Amputation',1500.00,10);
INSERT INTO OPERATION_TYPE VALUES ('TS','Tonsillectomy',700.00,7);
INSERT INTO OPERATION_TYPE VALUES ('LP','Laparoscopy',500.00,1);
INSERT INTO OPERATION_TYPE VALUES ('AR','Arthroscopy ',700.00,17);
REM***********************
REM ADMISSION TABLE
REM***********************
INSERT INTO ADMISSION VALUES (205,101,'2/2/2011','HB',114,'P','21/2/2011');
INSERT INTO ADMISSION VALUES (275,101,'1/9/2010','HY',115,'L','1/11/2010');
INSERT INTO ADMISSION VALUES (286,101,'3/5/2016','AR',116,'A','3/7/2016');
INSERT INTO ADMISSION VALUES (303,101,'3/4/2018','LA',125,'F', '13/5/2018');
INSERT INTO ADMISSION VALUES (298,103,'23/1/2016','TS',114,'L','24/04/2016');
INSERT INTO ADMISSION VALUES (299,103,'23/3/2018','AP',114,'L','23/4/2018');
INSERT INTO ADMISSION VALUES (305,103,'23/4/2018','HT',125,'F','29/5/2018');
INSERT INTO ADMISSION VALUES (321,103,'13/8/2018','AR',125,'F', '23/10/2018');
INSERT INTO ADMISSION VALUES (283,105,'3/12/2015','AR',116,'A','5/12/2015');
INSERT INTO ADMISSION VALUES (278,105,'1/1/2011','HB',115,'P','30/1/2011');
INSERT INTO ADMISSION VALUES (307,105,'3/4/2018','TS',125,'F', '13/5/2018');
INSERT INTO ADMISSION VALUES (276,106,'24/8/2010','LA',114,'P','15/9/2010');
INSERT INTO ADMISSION VALUES (287,106,'3/5/2016','TS',114,'A','3/6/2016');
INSERT INTO ADMISSION VALUES (274,109,'1/9/2019','AP',114,'P','9/9/2019');
INSERT INTO ADMISSION VALUES (288,109,'23/5/2016','LO',114,'F','3/07/2016');
INSERT INTO ADMISSION VALUES (301,112,'13/4/2018','AP',125,'F','16/4/2018');
INSERT INTO ADMISSION VALUES (304,112,'23/4/2019','LO',114,'L','23/5/2019');
INSERT INTO ADMISSION VALUES (279,113,'3/9/2010','TS',115,'F','10/9/2010');
INSERT INTO ADMISSION VALUES (284,113,'3/12/2015','HY',116,'A','03/01/2016');
INSERT INTO ADMISSION VALUES (285,113,'3/5/2016','HT',116,'A','3/6/2016');
INSERT INTO ADMISSION VALUES (300,113,'23/4/2018','AR',114,'L','25/6/2018');
INSERT INTO ADMISSION VALUES (306,113,'13/8/2018','AP',125,'L', '13/9/2018');
INSERT INTO ADMISSION VALUES (277,114,'20/9/2010','AP',115,'P','30/9/2010');
INSERT INTO ADMISSION VALUES (289,115,'11/4/2016','LO',114,'L','3/6/2016');
INSERT INTO ADMISSION VALUES (290,115,'5/7/2016','TS',114,'L','3/09/2016');
INSERT INTO ADMISSION VALUES (308,115,'23/3/2018','AR',114,'L','25/3/2018');
INSERT INTO ADMISSION VALUES (280,117,'13/9/2010','AP',115,'F','25/9/2010');
INSERT INTO ADMISSION VALUES (281,117,'3/9/2014','HB',116,'A','21/9/2014');
INSERT INTO ADMISSION VALUES (282,117,'3/12/2015','LA',116,'A','14/12/2015');
INSERT INTO ADMISSION VALUES (309,126,'23/3/2018','TS',125,'L', '13/5/2018');
INSERT INTO ADMISSION VALUES (310,127,'13/5/2018','AP',125,'L', '28/5/2018');
INSERT INTO ADMISSION VALUES (311,124,'3/5/2018','LO',125,'A', '23/5/2018');
INSERT INTO ADMISSION VALUES (312,127,'21/6/2019','LO',125,'L','22/8/2019');
INSERT INTO ADMISSION VALUES (313,124,'22/6/2019','AP',125,'A','22/7/2019');
INSERT INTO ADMISSION VALUES (314,109,'21/6/2019','LO',125,'L','22/7/2019');
INSERT INTO ADMISSION VALUES (315,126,'12/6/2019','AP',125,'A','22/9/2019');
INSERT INTO ADMISSION VALUES (316,114,'22/7/2019','HB',125,'A','12/12/2019');
INSERT INTO ADMISSION VALUES (318,128,'3/5/2019','LA',116,'A','4/6/2019');
INSERT INTO ADMISSION VALUES (319,129,'23/3/2019','TS',125,'L', '13/4/2019');
INSERT INTO ADMISSION VALUES (320,130,'3/5/2019','LA',116,'F','4/6/2019');
INSERT INTO ADMISSION VALUES (328,119,'3/3/2019','TS',115,'N', '3/4/2019');
INSERT INTO ADMISSION VALUES (322,132,'3/5/2019','LA',116,'A','4/6/2019');
INSERT INTO ADMISSION VALUES (323,133,'23/3/2019','TS',125,'L', '13/4/2019');
INSERT INTO ADMISSION VALUES (324,131,'3/5/2018','LA',116,'F','4/5/2018');
INSERT INTO ADMISSION VALUES (325,118,'3/6/2019','TS',115,'P', '3/7/2019');
INSERT INTO ADMISSION VALUES (326,102,'3/5/2018','LA',116,'F','4/5/2018');
INSERT INTO ADMISSION VALUES (327,104,'3/6/2019','TS',115,'P', '3/7/2019');
INSERT INTO ADMISSION VALUES (339,107,'3/6/2019','TS',115,'P', '3/7/2019');
INSERT INTO ADMISSION VALUES (329,110,'3/6/2019','TS',115,'P', '3/7/2019');
INSERT INTO ADMISSION VALUES (330,111,'3/6/2019','TS',115,'P', '3/7/2019');
INSERT INTO ADMISSION VALUES (331,116,'3/6/2019','TS',115,'P', '3/7/2019');
INSERT INTO ADMISSION VALUES (332,121,'21/6/2019','TS',125,'L','22/7/2019');
INSERT INTO ADMISSION VALUES (333,123,'22/7/2019','AP',125,'A','22/9/2019');
INSERT INTO ADMISSION VALUES (334,134,'21/8/2019','AP',115,'L','22/12/2019');
INSERT INTO ADMISSION VALUES (335,128,'12/8/2020','AP',115,'A',NULL);
INSERT INTO ADMISSION VALUES (336,125,'22/7/2020','HB',115,'A',NULL);
INSERT INTO ADMISSION VALUES (337,120,'21/8/2020','AP',116,'L',NULL);
INSERT INTO ADMISSION VALUES (338,130,'22/7/2020','AP',125,'N',NULL);
INSERT INTO ADMISSION VALUES (340,131,'22/8/2020','AP',125,'N',NULL);
INSERT INTO ADMISSION VALUES (341,122,'22/8/2020','AP',125,'N',NULL);
INSERT INTO ADMISSION VALUES (490,139,'11/8/2020','AP',125,'F',NULL);
INSERT INTO ADMISSION VALUES (491,140,'7/9/2020','AP',138,'F',NULL);
REM***********************
REM OPERATION TABLE
REM***********************
INSERT INTO OPERATION VALUES (317,'HB',205,'4/2/2011',110,111);
INSERT INTO OPERATION VALUES (355,'LA',276,'25/8/2010',103,111);
INSERT INTO OPERATION VALUES (363,'AP',276,'3/9/2010',103,111);
INSERT INTO OPERATION VALUES (360,'AP',277,'22/9/2010',103,111);
INSERT INTO OPERATION VALUES (361,'AP',274,'2/9/2010',103,111);
INSERT INTO OPERATION VALUES (362,'HT',275,'3/9/2010',110,112);
INSERT INTO OPERATION VALUES (364,'AP',279,'3/9/2010',103,111);
INSERT INTO OPERATION VALUES (365,'AP',280,'6/9/2010',103,111);
INSERT INTO OPERATION VALUES (366,'HB',281,'6/9/2014',103,111);
INSERT INTO OPERATION VALUES (367,'HY',284,'6/12/2015',103,111);
INSERT INTO OPERATION VALUES (368,'LO',285,'6/5/2016',118,112);
INSERT INTO OPERATION VALUES (369,'AP',286,'6/5/2016',118,112);
INSERT INTO OPERATION VALUES (370,'TS',287,'7/5/2016',118,112);
INSERT INTO OPERATION VALUES (371,'LA',288,'26/5/2016',110,111);
INSERT INTO OPERATION VALUES (372,'LO',289,'16/4/2016',110,111);
INSERT INTO OPERATION VALUES (373,'TS',290,'6/5/2016',110,111);
INSERT INTO OPERATION VALUES (381,'TS',298,'26/2/2016',110,111);
INSERT INTO OPERATION VALUES (382,'AP',299,'26/3/2018',110,111);
INSERT INTO OPERATION VALUES (383,'TS',300,'26/5/2018',110,111);
INSERT INTO OPERATION VALUES (384,'TS',309,'16/4/2018',110,111);
INSERT INTO OPERATION VALUES (385,'LO',309,'26/3/2018',110,111);
INSERT INTO OPERATION VALUES (386,'AP',310,'18/5/2018',110,111);
INSERT INTO OPERATION VALUES (387,'AP',311,'4/5/2018',110,111);
INSERT INTO OPERATION VALUES (388,'LO',311,'11/5/2018',110,111);
INSERT INTO OPERATION VALUES (389,'AP',315,'13/6/2019',118,111);
INSERT INTO OPERATION VALUES (390,'HB',316,'23/7/2019',118,111);
INSERT INTO OPERATION VALUES (391,'LO',312,'22/6/2019',118,111);
INSERT INTO OPERATION VALUES (392,'HT',341,'28/8/2019',118,112);
INSERT INTO OPERATION VALUES (393,'HT',340,'27/8/2019',118,112);
INSERT INTO OPERATION VALUES (394,'LO',491,'26/4/2020',103,112);
REM***********************
REM OBSERVATION TABLE
REM***********************
INSERT INTO OBSERVATION VALUES (205,'2/2/2011',1500,'Temp',38,114);
INSERT INTO OBSERVATION VALUES (274,'4/9/2010',0601,'Temp',39,116);
INSERT INTO OBSERVATION VALUES (275,'1/9/2010',1400,'Pulse',64,115);
INSERT INTO OBSERVATION VALUES (275,'1/9/2010',1400,'Temp',38,115);
INSERT INTO OBSERVATION VALUES (275,'3/9/2010',1800,'Temp',40,116);
INSERT INTO OBSERVATION VALUES (275,'3/9/2010',2200,'Temp',40,116);
INSERT INTO OBSERVATION VALUES (275,'4/9/2010',0610,'Pulse',82,116);
INSERT INTO OBSERVATION VALUES (275,'4/9/2010',0610,'Temp',38,116);
INSERT INTO OBSERVATION VALUES (277,'24/9/2010',0600,'Temp',39,115);
INSERT INTO OBSERVATION VALUES (284,'5/12/2015',0600,'Temp',39,115);
INSERT INTO OBSERVATION VALUES (284,'5/12/2015',0600,'Pulse',89,115);
INSERT INTO OBSERVATION VALUES (284,'6/12/2015',0600,'Temp',37,115);
INSERT INTO OBSERVATION VALUES (284,'6/12/2015',0600,'Pulse',87,115);
INSERT INTO OBSERVATION VALUES (285,'7/5/2016',0600,'Temp',38,115);
INSERT INTO OBSERVATION VALUES (285,'8/5/2016',0600,'Temp',38,115);
INSERT INTO OBSERVATION VALUES (285,'8/5/2016',0600,'Pulse',82,115);
INSERT INTO OBSERVATION VALUES (285,'9/5/2016',0600,'Temp',37,115);
INSERT INTO OBSERVATION VALUES (286,'7/5/2016',0600,'Temp',39,125);
INSERT INTO OBSERVATION VALUES (286,'8/5/2016',0600,'Temp',33,125);
INSERT INTO OBSERVATION VALUES (286,'8/5/2016',0600,'Pulse',86,125);
INSERT INTO OBSERVATION VALUES (286,'9/5/2016',0600,'Temp',36,125);
INSERT INTO OBSERVATION VALUES (287,'7/5/2016',0600,'Temp',35,115);
INSERT INTO OBSERVATION VALUES (287,'8/5/2016',0600,'Temp',37,115);
INSERT INTO OBSERVATION VALUES (287,'8/5/2016',0600,'Pulse',82,125);
INSERT INTO OBSERVATION VALUES (287,'9/5/2016',0600,'Temp',37,125);
INSERT INTO OBSERVATION VALUES (289,'19/5/2016',0600,'Temp',39,115);
INSERT INTO OBSERVATION VALUES (289,'20/5/2016',1400,'Temp',38,115);
INSERT INTO OBSERVATION VALUES (289,'22/5/2016',0800,'Temp',37,115);
INSERT INTO OBSERVATION VALUES (289,'26/5/2016',0700,'Temp',37,115);
INSERT INTO OBSERVATION VALUES (289,'29/5/2016',0700,'Temp',38,115);
INSERT INTO OBSERVATION VALUES (300,'23/4/2018',1400,'Pulse',74,115);
INSERT INTO OBSERVATION VALUES (300,'23/4/2018',1400,'Temp',38,115);
INSERT INTO OBSERVATION VALUES (300,'23/4/2018',1800,'Temp',30,116);
INSERT INTO OBSERVATION VALUES (300,'23/4/2018',2200,'Temp',40,116);
INSERT INTO OBSERVATION VALUES (300,'24/4/2018',0610,'Pulse',82,116);
INSERT INTO OBSERVATION VALUES (300,'24/4/2018',0610,'Temp',38,116);
INSERT INTO OBSERVATION VALUES (303,'13/4/2018',1400,'Pulse',64,125);
INSERT INTO OBSERVATION VALUES (303,'13/4/2018',1400,'Temp',38,125);
INSERT INTO OBSERVATION VALUES (303,'13/4/2018',1800,'Temp',30,125);
INSERT INTO OBSERVATION VALUES (303,'23/4/2018',2200,'Temp',40,116);
INSERT INTO OBSERVATION VALUES (303,'23/4/2018',0610,'Pulse',82,116);
INSERT INTO OBSERVATION VALUES (303,'23/4/2018',0610,'Temp',38,116);
INSERT INTO OBSERVATION VALUES (311,'3/5/2018',1400,'Pulse',54,115);
INSERT INTO OBSERVATION VALUES (311,'4/5/2018',1400,'Temp',38,115);
INSERT INTO OBSERVATION VALUES (311,'3/5/2018',1800,'Temp',40,116);
INSERT INTO OBSERVATION VALUES (311,'4/5/2018',2200,'Temp',41,116);
INSERT INTO OBSERVATION VALUES (311,'4/5/2018',1800,'Temp',39,116);
INSERT INTO OBSERVATION VALUES (311,'5/5/2018',0610,'Pulse',72,116);
INSERT INTO OBSERVATION VALUES (311,'5/5/2018',0610,'Temp',38,116);
INSERT INTO OBSERVATION VALUES (310,'13/5/2018',1400,'Pulse',84,125);
INSERT INTO OBSERVATION VALUES (310,'13/5/2018',1400,'Temp',28,125);
INSERT INTO OBSERVATION VALUES (310,'14/5/2018',1800,'Temp',60,125);
INSERT INTO OBSERVATION VALUES (310,'15/5/2018',2200,'Temp',40,116);
INSERT INTO OBSERVATION VALUES (310,'16/5/2018',0610,'Pulse',92,116);
INSERT INTO OBSERVATION VALUES (310,'16/5/2018',0610,'Temp',35,116);
INSERT INTO OBSERVATION VALUES (341,'22/8/2019',0610,'Temp',39,116);
INSERT INTO OBSERVATION VALUES (340,'25/8/2019',0610,'Temp',39,116);
INSERT INTO OBSERVATION VALUES (340,'25/8/2019',0610,'Pulse',75,116);
INSERT INTO OBSERVATION VALUES (340,'26/8/2019',0610,'Temp',37,116);
INSERT INTO OBSERVATION VALUES (340,'26/8/2019',0610,'Pulse',70,116);
INSERT INTO OBSERVATION VALUES (340,'27/8/2019',0610,'Pulse',68,116);
INSERT INTO OBSERVATION VALUES (340,'27/8/2019',0610,'Temp',37,116);
INSERT INTO OBSERVATION VALUES (340,'29/8/2019',0610,'Pulse',73,116);
INSERT INTO OBSERVATION VALUES (490,'17/4/2020',0600,'Temp',38,125);
INSERT INTO OBSERVATION VALUES (490,'18/4/2020',0600,'Temp',37,125);
INSERT INTO OBSERVATION VALUES (490,'19/4/2020',0600,'Temp',38,125);
...ANSWER
Answered 2021-Jun-03 at 16:53I'm assuming you don't really need a cross join of 'person' with 'person'. So I'm dropping that logic from the sources.
I don't have and Oracle instance to work with, but I believe the code below, which uses a case statement to achieve your conditional need, should work for you:
QUESTION
An image of the table to retrieve the data from:
REM ADMISSION TABLE
INSERT INTO ADMISSION VALUES (205,101,'2/2/2011','HB',114,'P','21/2/2011');
...ANSWER
Answered 2021-Jun-03 at 09:47count group by patient_id and use FETCH FIRST 1 ROWS ONLY:
QUESTION
I am trying to send out an email with node mailer, and it is sending the email, but I am trying to use an image in there, a base64 image. I've converted the image to base64, and done this:
...ANSWER
Answered 2021-Jun-02 at 16:51var base64 = `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`
html: "
Thank you "
QUESTION
I'm trying to parse this .txt file in R: https://ftp.expasy.org/databases/cellosaurus/cellosaurus.txt
It's essentially a single column data frame of some ~2 million rows, with each entity being described by multiple rows and bookended by rows containing the string "//".
Ideally, I could capture each entity, made up of multiple rows, as a list element by splitting at "//", but I'm not sure of the most efficient way to go about this.
Any help is much appreciated.
EDIT:
Here's a snippet of what I'm working with:
...ANSWER
Answered 2021-Jun-02 at 11:06Here is one solution using data.table
.
QUESTION
.
My goal is to determine the bar location of the lowest-low
since the highest-high[lookback]
.
I have no idea why it is not possible to plug the value of hb
into lowestbars()
, although my sense is that highestbars()
is creating a variable type that is unacceptable to lowestbars()
?
ANSWER
Answered 2021-May-23 at 03:57It's probably because some built in functions can't accept a time series variable as input, which hb is, a series int as opposed to a var int or input int.
QUESTION
I have the following two datasets:
...ANSWER
Answered 2021-May-20 at 07:50I think the argument of your includes
method here shouldn't be an array here, the check should rather be other way around.
Community Discussions, Code Snippets contain sources that include Stack Exchange Network
Vulnerabilities
No vulnerabilities reported
Install hb
For all platforms you will need:.
Supported ANSI C89 compiler
GNU Make (3.81 or upper)
Harbour sources
You can fine-tune Harbour builds with below listed environment variables. You can add most of these via the GNU Make command-line also, using make VARNAME=value syntax. These settings are optional and all settings are case-sensitive.
For all platforms you will need:. Use hbmk2 to build your app from source. It's recommended to put it in the PATH (e.g. by using set PATH=C:\hb\bin;%PATH% on Windows). See hbmk2 documentation, with examples.
Harbour binaries Either a Harbour binary distribution or a local Harbour build will be okay. If you're reading this text, it's likely you have one of these already.
Supported ANSI C89 compiler You need to add your compiler of choice to the PATH — and configure it according to its instructions. If you use the official Harbour binary distribution on Windows, you already have the MinGW C compiler embedded in the installation, which will automatically be used, so you don't have to make extra steps here.
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